We extract diamond specifications, fine jewelry variants, pricing signals, and daily deal promotions from Superjeweler. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Rings & Bands objects from superjeweler.com. All fields typed and schema-versioned.
"sku": "SJ-R-10492", "title": "1 Carat Diamond Solitaire Ring in 14K White Gold", "metal_type": "14K White Gold", "diamond_carat": 1.0, "clarity": "I1-I2", "colour": "J-K", "price": 999.99, "sizes_available": "['5', '6', '7', '8', '9']", "in_stock": true
| # | sku | title | metal_type | diamond_carat | clarity | colour |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Earrings & Necklaces objects from superjeweler.com. All fields typed and schema-versioned.
"sku": "SJ-E-88321", "title": "Sapphire and Diamond Halo Stud Earrings", "gemstone_type": "Sapphire", "stone_cut": "Round", "setting_type": "Prong", "price": 249.99, "stock_status": "In Stock", "image_url": "https://example.com/img.jpg"
| # | sku | title | gemstone_type | stone_cut | setting_type | chain_length |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Diamond Specs objects from superjeweler.com. All fields typed and schema-versioned.
"sku": "SJ-D-4412", "shape": "Princess", "carat": 1.5, "colour_grade": "H", "clarity_grade": "VS2", "cut_grade": "Excellent", "certification": "IGI", "fluorescence": "None", "symmetry": "Very Good"
| # | sku | shape | carat | colour_grade | clarity_grade | cut_grade |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Deals objects from superjeweler.com. All fields typed and schema-versioned.
"sku": "SJ-R-10492", "current_price": 999.99, "original_price": 2999.99, "discount_pct": 66, "daily_deal_flag": true, "deal_expiry": "2023-11-01T23:59:59Z", "clearance_flag": false, "coupon_eligible": false
| # | sku | current_price | original_price | discount_pct | daily_deal_flag | deal_expiry |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from superjeweler.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "SJ-R-10492", "reviewer_name": "Sarah M.", "rating": 5, "review_date": "2023-09-15", "review_text": "Beautiful ring, sparkles perfectly.", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | reviewer_name | rating | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline captures complex jewelry attributes—from precise diamond grading and metal alloys to dynamic daily deals and clearance shifts—normalised into flat, queryable records.
Capture every combination of ring size, metal type, and carat weight as distinct records or nested arrays.
Parse unstructured descriptions into structured fields for cut, colour, clarity, and carat weight.
Monitor flash sales, countdown timers, and temporary price drops with high-frequency scraping runs.
Track stock depth and clearance status across thousands of SKUs to forecast inventory depletion.
Extract URLs for primary product images, alternate angles, and certification documents.
Aggregate customer feedback, star ratings, and verified purchase flags across the entire catalogue.
Preserve the exact site taxonomy to categorise items correctly from fine jewelry to fashion pieces.
Compute exact absolute and percentage discounts between list price and current selling price.
Compare current scrapes against historical hashes to deliver only updated prices and new inventory.
Brief in. Clean data out.
Provide target categories, search terms, or deal pages. We map the required attributes and variants.
We configure Scrapy crawlers with custom parsing logic for Superjeweler's specific DOM structure.
Schema validation ensures diamond grades, prices, and variant matrices are perfectly formatted.
Clean JSON, CSV, or Parquet pushed to your S3 bucket or data warehouse on an automated schedule.
Extracting fine jewelry data requires handling complex variant matrices and dynamic promotional states.
A single ring might have 10 sizes and 4 metal types. We iterate through frontend state changes to capture the exact price and SKU for every possible permutation.
Jewelry descriptions often mix marketing copy with technical specs. We use regex and NLP to extract precise carat weights, clarity grades, and metal purities into strict schema fields.
Superjeweler frequently runs time-bound promotions. Our pipelines can run at hourly cadences to capture deal prices before the countdown timers expire.
We bypass thumbnail galleries to locate and extract the highest resolution image URLs available in the source code, essential for visual AI training.
Clearance sections often contain thousands of items. We bypass frontend display limits by directly querying underlying API endpoints where available.
Jewelry retailers track Superjeweler's aggressive discounting and daily deals to adjust their own promotional pricing.
Analysts monitor the popularity of specific gemstone cuts, metal types, and carat ranges based on review velocity.
Publishers populate their deal aggregation sites with structured data extracted directly from Superjeweler's clearance section.
Machine learning teams use high-res jewelry images paired with structured attribute data to train visual search models.
Supply chain analysts track stock-out rates across different ring sizes and metal types to model consumer demand.
Quants aggregate carat, cut, colour, and clarity data against retail prices to build automated valuation algorithms.
"Superjeweler offers a massive catalogue of accessible fine jewelry, but extracting precise diamond grades and metal variants requires a structured schema."
Scraping fine jewelry is complex due to the sheer volume of variant permutations—ring sizes, metal types, and carat weights. DataFlirt normalises this multidimensional data into flat, queryable records, handling daily deal timers and clearance shifts automatically. Your engineers get clean data, not maintenance tickets.
Everything supported by our superjeweler.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright manages JavaScript execution required for variant price loading.
US-based residential IPs ensure reliable access and prevent IP bans during high-frequency deal monitoring runs.
Pipelines run on AWS Lambda and ECS, orchestrated by Airflow for strict delivery SLAs and automated retries.
Data delivered to where your team already works — no new tooling required.
About superjeweler.com scraping, legality, and pipeline operations.
Ask us directly →Yes. Our scrapers iterate through the frontend selection logic to capture the specific price, SKU, and availability for every valid combination of size and metal type on a product page.
We can configure pipelines to run at high frequencies (e.g., hourly) to detect new daily deals, capturing the discounted price and the exact expiration timestamp.
Yes. We parse the product specifications to extract structured fields for carat weight, cut, colour, and clarity, even when they are embedded in paragraph text.
We extract the direct URLs to the highest resolution images available on the site, which you can then download or hotlink as needed.
We capture the stock status for every item and variant. You can choose to include out-of-stock items in your delivery or filter them out entirely.
Absolutely. By running the pipeline daily or weekly, we maintain a historical price log, allowing you to track exactly when and by how much an item was discounted.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually tracking daily deals and variant prices. DataFlirt builds and manages the extraction infrastructure so you can focus on market analysis.
